Table of Contents

  1. Foundations of Data Analysis and Python
  2. Exploratory Data Analysis
  3. Frequency Distribution, Central Tendency, Variability
  4. Unravelling Statistical Relationships
  5. Estimation and Confidence Intervals
  6. Hypothesis and Significance Testing 
  7. Statistical Machine Learning
  8. Unsupervised Machine Learning
  9. Linear Algebra, Nonparametric Statistics, and Time Series Analysis
  10. Generative AI and Prompt Engineering
  11. Real World Statistical Applications